UDA

UDA, or Unsupervised Domain Adaptation, is a machine learning technique that helps models perform well on new data that differs from their training data. For example, a model trained to recognize objects in sunny outdoor photos can struggle with cloudy or indoor images. UDA techniques allow the model to adapt to these new environments without needing labeled examples from them. It does this by finding common features between the original and new data, enabling the model to generalize better and make accurate predictions across different settings.